CLiMB: Computational Linguistics for Metadata Building

1. Center for Research on Information Access Columbia University Libraries CLiMB: Computational Linguistics for Metadata Building Judith L. Klavans

2. June 2003 to November 2003 Four areas • Collections • Technology • Users and Uses • Interface Tools November - Waters/Lodato for next steps Judith L. Klavans

3. Goals of December Meeting • Conclusion from last meeting: CLiMB still a research platform • Explore potential platforms for testing CLiMB tools • What is the possibility of working with ArtStor? • Changes in Personnel Judith L. Klavans

4. Problems in Image Access • Cataloging digital images • Traditional approach: manual expertise • labor intensive • expensive • Can automated techniques help? Judith L. Klavans

5. CLiMB Technical Contribution • CLiMB will identify and extract • proper nouns • terms and phrases • from text related to an image: September 14, 1908, the basis of the Greenes' final design had been worked out. It featured a radically informal, V-shaped plan (that maintained the original angled porch) and interior volumes of various heights, all under a constantly changing roofline that echoed the rise and fall of the mountains behind it. The chimneys and foundation would be constructed of the sandstone bouldersthat comprised the local geology, and the exterior of the house would be sheathed in stained split-redwood shakes. —Edward R. Bosley. Greene & Greene. London : Phaidon, 2000. p. 127 Judith L. Klavans

6. Can we harvest image descriptors? angled porch v-shaped plan sandstone boulders Judith L. Klavans

7. Progress and Planning • Collections • Technology • Users and Uses • Interface Tools Judith L. Klavans

8. Judith L. Klavans

9. Progress and Planning • Collections • Technology • Users and Uses • Interface Tools Judith L. Klavans

10. Text Analysis and Filtering • Divide text into words and phrases • Gather features for each word and phrase • E.g. Is it in the AAT? Is it very frequent? • Develop formulae using this information • Use formulae to rank for usefulness as potential metadata Judith L. Klavans

11. What Features do we Track? • Lexical features • Proper noun, common noun • Relevancy to domain • Text Object Identifier (TOI) • Presence in the Art & Architecture Thesaurus • Presence in the back-of-book index • Statistical observations • Frequency in the text • Frequency across a larger set of texts, within and outside the domain Judith L. Klavans

12. Problem: Too much Data! • How should the output be filtered? • What filtering helps additional text processing (e.g. for text segmentation)? • What filtering matches what users think? Judith L. Klavans

13. Techniques for Filtering • Take an initial guess • Collect input from users • Alter formulae based on feedback • Use automatic techniques to guess (machine-learning) • Collect input from users • Run programs to make predictions based on given opinions (Bayesian networks, classifiers, decision trees) • The CLiMB approach: Use both techniques! Judith L. Klavans

14. Next Steps • Filter “given” information (already in catalogue record if you are lucky enough to have one!) • What does CLiMB get that is new? • How much is useful? • What is the “cost”? Judith L. Klavans

15. Progress and Planning • Collections • Technology • Users and Uses • Interface Tools Judith L. Klavans

16. Formative Evaluation Meeting • At the advice of External Advisory Board • October 17, 2003 • Goals: • Get early feedback from many user types • Incorporate that feedback into CLiMB toolset • Help shape next steps Judith L. Klavans

17. CLiMB Project Team - Judith Klavans - Roberta Blitz - Rebecca Passonneau - Angela Giral - Vera Horvath - David Elson - Bob Wolven - Stephen Davis - Mark Weber CLiMB: External Advisory Board - Jeff Cohen (Bryn Mawr) - Carl Lagoze (Cornell) - Merrilee Proffitt (RLG) Invitees - Robert Carlucci (Columbia) - Terry Catapano (Columbia) - Paula Gabbard (Columbia) - Deborah Kempe (Frick) - Doug Oard (UMd) Could not Attend Tony Gill (Mellon) Abby Goodrum (Syracuse) Elisa Lanzi (Smith) Formative Evaluation - Attendees Judith L. Klavans

18. Results from Formative Evaluation • Best – Humans select, CLiMB selects • Cordelia A. Culbertson • Better - Humans select, CLiMB might not • Ludowici-Celadon Company • Better – Humans might not but CLiMB selects • house, Tichenor house, most significant house • Good – Humans do not select, CLiMB does not • problem, time Judith L. Klavans

19. Research Questions • Will CLiMB metadata help users get access to the digital images they want? • Will these terms help catalogers provide this access? • How well are the CLiMB tools performing in providing required metadata? Judith L. Klavans

20. Use Results for Improvement • Determine ways to better filter CLiMB results • Use input for improving ranking Judith L. Klavans

21. Progress and Planning • Collections • Technology • Users and Uses • Interface Tools Judith L. Klavans

22. Interface Tools • Planning the new interface for image professionals to prepare CLiMB metadata from texts • For catalogers / metadata specialists and visual resources professionals • Goals • to provide a platform for a wider community • to be able to collect feedback on CLiMB at a wider level • to complete the CLiMB interface “deliverable” Judith L. Klavans

23. Interface Tools – Stay Tuned! • CLiMB toolset currently implemented with textual interface • Fully-functional shell • New graphical user interface (GUI) can be built on top of existing codebase • Perl/Tk • Design • Initiating design phase now • Consulting metadata and image specialists Judith L. Klavans

24. Next Steps • External Advisory Board– June 2004 • Select project directions • Potential partners Judith L. Klavans

25. Thank you! www.columbia.edu/cu/cria